I have created a alternative GC for python it's called VGC no GIL bottleneck

VGC (Virtual Garbage Collector) is a next-generation memory framework that replaces Python’s traditional garbage collection with a parallel, logic-driven model.

Instead of reference counting or tracing, VGC tracks object lifecycles using a 3-bit checkpoint system and logic gates (AND/OR/XOR), enabling deterministic, real-time memory management.

It runs under a single interpreter and partitions workloads dynamically across CPU cores and threads. Each object lives in one of three virtual zones — Red (rarely used), Green (frequently accessed), and Blue (medium activity) — each optimized for a specific mutation–lifetime balance. This design allows VGC to achieve hardware-level concurrency while maintaining memory safety and predictability.

I tried core based partition sorting approach which will sort based on the value of the num as min, mid, max perfect for quad core processors …. While three core split as low, mid, high value remaining core stay idle may be way of Approach trying different methods like this might improve the processing speed and reduce the time complexity hope for the best ….

For dual core it will sort as low and high valued numbers based on the indexing those values in the core count not suitable for single core, but far more better with octa core, good at quad average expected speed at dual core processors

By Sunday 09/11/25 i have tested by PPE (Partition And Parallel Execution) prototype which complete the 1 Million Loop Iteration at 0.569300 milli sec. And For Recursion. to run 50,000 Recursion Depth at 0.150700 milli sec. It runs under 79% of CPU usage both Dual Core Partition (2 core, 4 thread) total core used (4 core, 8 thread) and it is an Octa core processor (8 core, 16 threads)

Here’s how it really works behind. It just about how we utilise the hardware resources instead of the wasting that remaining core on multi core processor we utilise them like this for heavy operation

Summary :

Dual core –> 2 partition and parallel execution

Quad core –> 4 partition and parallel execution

Hexa core –> 6 partition and parallel execution

Octa core –> 8 partition and parallel execution

Deca core –> 10 partition and parallel execution

Working principle of Partition and Parallel Execution which improves the execution time reducing time complexity also we utilised the hardware CPU cores well also enables systems of well functional scalable, reliable, maintainable systems in future thank you.

Actively working on PPE and VGC once its get done it is going to opensource for python !! GG

Acheived 0.000175 sec / 0.175300 milli sec process of 100 K loops iteration without partition and Run with single core after the internal optimization of the malloc function in the architecture

Those are not big claim any more now i have actual working prototype which is fast also well scalable based on the N number of core …. Like Nvidia Nvlink spine scales GPU the main primary goal of this project is to utilise the hardware resources as much we can …..

Do you have any doubts regarding this proto-type project ?

Guys what is your point of view on PPE runtime architecture…

Achieving the average execution speed of 5.96 milliseconds 0.00596 seconds to run 4 Million Loops iterations with 2 partition… and parallel execution both of the Architecture VGC and PPE still under development process

PPE (partition and parallel execution) is a Run time Architecture

VGC (Garbage Collector) GC Architecture

Prototype Architecture was successfully completed also it is going to be released as OpenSource on Arxiv Pre-Prints Anyone who wants to use it or implement it they can use for free since this is my first open source intial stage working prototype of Runtime Architecture also the sample test code will be uploaded on my GitHub Repo separately created for Arxiv as VGC-Arxiv once done I will update that later on this discussion…

As Python explores reduced-GIL execution models, minimizing GC interaction and object churn becomes increasingly important

My POV on removing GIL on python 3.14

  1. Removing the GIL makes GC harder, not easier.
  2. No-GIL Python without GC redesign is impossible.
  3. CPython is avoiding the problem via isolation, not by magic.
  4. GC will be the dominant cost in no-GIL scenarios.
  5. My VGC ideas align with the direction, not only at the implementation

in Simple term :

No-GIL is an execution problem; GC is the correctness problem.

Let’s further improve the VGC, thoroughly test and enrich it, and integrate it with CPython

Intial stage working prototype has been completed also it is licensed under CC0 in Arxiv and MIT in GitHub (opensource)

2512.23768v1.pdf https://share.google/CbIlWZKuLlHWueE8D

//VGC_sample_code

#include iostream

#include <unordered_map>

#include vector

#include cstdint

#include functional

#include string

// VIRTUAL GARBAGE COLLECTOR (VGC) STATE DEFINITIONS:-

/**

* VGC State Machine - 3-bit encoding for object lifecycle management

*

* Each state represents a distinct phase in the object’s lifecycle,

* guiding the collector’s decisions about memory management.

*/

enum class VGC_State : uint8_t {

IDLE      = 0b000,  // Object is sleeping, waiting for activation

ACTIVE    = 0b001,  // Object is in active use, keep alive

PROMOTE   = 0b010,  // Candidate for moving to a higher-priority zone

DEMOTE    = 0b011,  // Candidate for moving to a lower-priority zone

PERSIST   = 0b100,  // Long-lived object, maintain regardless of zone

DEFERRED  = 0b101,  // Collection deferred to next cycle

MARKED    = 0b110,  // Flagged for potential deletion

EXPIRED   = 0b111   // Ready for immediate reclamation

};

/**

* Memory Zone Classification

* Objects are assigned to zones based on their expected lifetime

* and access patterns, enabling differentiated collection strategies.

*/

enum class MemoryZone : uint8_t {

RED   = 0b001,  // Short-lived, high-turnover objects

GREEN = 0b010,  // Medium-lived, regular objects

BLUE  = 0b100   // Long-lived, persistent objects

};

/**

* Represents an object tracked by the VGC system

* Each object carries metadata that informs the collector’s decisions,

* balancing immediate needs with long-term memory health.

*/

struct VGC_Object {

uint32_t id;           // Unique identifier for the object

uint8_t  zone_mask;    // Memory zone assignment (R/G/B mask)

uint8_t  state;        // Current lifecycle state (3-bit encoding)



// Helper function for human-readable state display

std::string state_name() const {

    switch (static_cast<VGC_State>(state)) {

        case VGC_State::IDLE:     return "IDLE";

        case VGC_State::ACTIVE:   return "ACTIVE";

        case VGC_State::PROMOTE:  return "PROMOTE";

        case VGC_State::DEMOTE:   return "DEMOTE";

        case VGC_State::PERSIST:  return "PERSIST";

        case VGC_State::DEFERRED: return "DEFERRED";

        case VGC_State::MARKED:   return "MARKED";

        case VGC_State::EXPIRED:  return "EXPIRED";

        default:                  return "UNKNOWN";

    }

}



// Helper function for human-readable zone display

std::string zone_name() const {

    switch (zone_mask) {

        case static_cast<uint8_t>(MemoryZone::RED):   return "RED";

        case static_cast<uint8_t>(MemoryZone::GREEN): return "GREEN";

        case static_cast<uint8_t>(MemoryZone::BLUE):  return "BLUE";

        default: return "MIXED_ZONE";

    }

}

};

/**

* Virtual Garbage Collector Manager

* Implements a zone-aware collection strategy using a logic gate approach

* to determine object liveness based on state, zone, and pending operations.

*/

class VGC_Manager {

private:

// Storage for managed objects, keyed by object ID

std::unordered_map<uint32_t, VGC_Object> heap;



// Collection of callbacks to execute before sweeping

std::vector<std::function<void()>> pre_sweep_callbacks;



// Collection of callbacks to execute after sweeping

std::vector<std::function<void(size_t)>> post_sweep_callbacks;

public:

/\*\*

 \* Allocates a new object into the managed heap

 \* @param id     Unique identifier for the object

 \* @param zone   Memory zone assignment (Red/Green/Blue)

 \* @param initial_state Starting lifecycle state (defaults to ACTIVE)

 \*/

void allocate(uint32_t id, MemoryZone zone, VGC_State initial_state = VGC_State::ACTIVE) {

    if (heap.count(id)) {

        std::cerr << "Warning: Object " << id << " already exists. Overwriting.\\n";

    }

    

    VGC_Object new_object = {

        id,

        static_cast<uint8_t>(zone),

        static_cast<uint8_t>(initial_state)

    };

    

    heap\[id\] = new_object;

    std::cout << "Allocated object " << id 

              << " in " << new_object.zone_name() 

              << " zone with state: " << new_object.state_name() << "\\n";

}

/\*\*

 \* Core liveness evaluation logic

 \* Implements the VGC decision equation: O = (S & Z) | (S & P)

 \* Where: S = current state, Z = zone mask, P = pending operations mask

 \* This forms the heart of the collector's decision-making process,

 \* determining whether an object should survive the current collection cycle.

 \*/

bool evaluate_liveness(const VGC_Object& obj, uint8_t pending_mask = 0) const {

    uint8_t current_state = obj.state;

    uint8_t zone_mask = obj.zone_mask;

    uint8_t pending_ops = pending_mask;

    // Special case: EXPIRED objects must always be collected

    if (static_cast<VGC_State>(current_state) == VGC_State::EXPIRED) {

        return false;

    }

    // Special case: PERSIST objects survive regardless of other factors

    if (static_cast<VGC_State>(current_state) == VGC_State::PERSIST) {

        return true;

    }

    // Apply the core VGC liveness equation

    uint8_t liveness_score = (current_state & zone_mask) | (current_state & pending_ops);

    

    // Objects with any liveness indication survive

    return liveness_score > 0 || 

           static_cast<VGC_State>(current_state) == VGC_State::ACTIVE;

}

/\*\*

 \* Register a callback to execute before each sweep operation

 \*/

void register_pre_sweep_callback(std::function<void()> callback) {

    pre_sweep_callbacks.push_back(callback);

}

/\*\*

 \* Register a callback to execute after each sweep operation

 \* Callback receives the number of objects reclaimed

 \*/

void register_post_sweep_callback(std::function<void(size_t)> callback) {

    post_sweep_callbacks.push_back(callback);

}

/\*\*

 \* Perform a garbage collection sweep

 \* Identifies unreachable objects using the liveness evaluation logic

 \* and reclaims their memory, maintaining heap health.

 \*/

void sweep(uint8_t pending_mask = 0) {

    std::cout << "\\n--- Initiating VGC Collection Cycle ---\\n";

    

    // Execute pre-sweep hooks (e.g., pause application threads)

    for (const auto& callback : pre_sweep_callbacks) {

        callback();

    }

    // Identify objects that are no longer alive

    std::vector<uint32_t> objects_to_reclaim;

    for (const auto& \[id, obj\] : heap) {

        if (!evaluate_liveness(obj, pending_mask)) {

            objects_to_reclaim.push_back(id);

        }

    }

    // Report and reclaim identified objects

    if (!objects_to_reclaim.empty()) {

        std::cout << "Reclaiming " << objects_to_reclaim.size() 

                  << " object(s):\\n";

        

        for (uint32_t id : objects_to_reclaim) {

            const auto& obj = heap\[id\];

            std::cout << "  • Object " << id 

                      << " (Zone: " << obj.zone_name()

                      << ", State: " << obj.state_name() << ")\\n";

            heap.erase(id);

        }

    } else {

        std::cout << "No objects eligible for reclamation.\\n";

    }

    // Execute post-sweep hooks (e.g., resume application threads, update stats)

    for (const auto& callback : post_sweep_callbacks) {

        callback(objects_to_reclaim.size());

    }

    

    std::cout << "--- Collection Cycle Complete ---\\n";

}

/\*\*

 \* Transition an object to a new lifecycle state

 \* @param id        Object identifier

 \* @param new_state Target state for the transition

 \*/

void transition_state(uint32_t id, VGC_State new_state) {

    auto it = heap.find(id);

    if (it != heap.end()) {

        VGC_State old_state = static_cast<VGC_State>(it->second.state);

        it->second.state = static_cast<uint8_t>(new_state);

        

        std::cout << "Object " << id 

                  << " transitioned: " 

                  << it->second.state_name()

                  << " (was: ";

        

        // Create temporary object to get old state name

        VGC_Object temp = it->second;

        temp.state = static_cast<uint8_t>(old_state);

        std::cout << temp.state_name() << ")\\n";

    } else {

        std::cerr << "Error: Cannot transition state. Object " 

                  << id << " not found.\\n";

    }

}

/\*\*

 \* Display current heap status in a human-readable format

 \*/

void display_status() const {

    std::cout << "\\n=== VGC Heap Status ===\\n";

    std::cout << "Total Managed Objects: " << heap.size() << "\\n";

    

    if (heap.empty()) {

        std::cout << "Heap is empty.\\n";

        return;

    }

    // Display summary by zone

    std::cout << "\\nZone Distribution:\\n";

    size_t red_count = 0, green_count = 0, blue_count = 0;

    

    for (const auto& \[id, obj\] : heap) {

        if (obj.zone_mask == static_cast<uint8_t>(MemoryZone::RED)) red_count++;

        else if (obj.zone_mask == static_cast<uint8_t>(MemoryZone::GREEN)) green_count++;

        else if (obj.zone_mask == static_cast<uint8_t>(MemoryZone::BLUE)) blue_count++;

    }

    

    std::cout << "  RED Zone (Short-lived):   " << red_count << " objects\\n";

    std::cout << "  GREEN Zone (Medium-lived): " << green_count << " objects\\n";

    std::cout << "  BLUE Zone (Long-lived):    " << blue_count << " objects\\n";

    // Display detailed object listing

    std::cout << "\\nDetailed Object List:\\n";

    std::cout << "ID     | Zone   | State      | Alive?\\n";

    std::cout << "-------|--------|------------|--------\\n";

    

    for (const auto& \[id, obj\] : heap) {

        bool is_alive = evaluate_liveness(obj);

        std::cout << std::setw(6) << id << " | "

                  << std::setw(6) << obj.zone_name() << " | "

                  << std::setw(10) << obj.state_name() << " | "

                  << (is_alive ? "YES" : "NO") << "\\n";

    }

    std::cout << "======================================\\n";

}

/\*\*

 \* Get the current number of managed objects

 \*/

size_t object_count() const {

    return heap.size();

}

};

// DEMONSTRATION OF THE VGC SYSTEM

int main() {

VGC_Manager collector;



// Register some callbacks to demonstrate extensibility

collector.register_pre_sweep_callback(\[\]() {

    std::cout << "\[Pre-sweep\] Pausing application threads...\\n";

});



collector.register_post_sweep_callback(\[\](size_t reclaimed_count) {

    std::cout << "\[Post-sweep\] Resuming application threads. "

              << reclaimed_count << " objects reclaimed.\\n";

});

std::cout << "=== Virtual Garbage Collector Demonstration ===\\n\\n";



// Phase 1: Object Allocation with Zone Assignment

std::cout << "Phase 1: Allocating Objects into Zones\\n";

collector.allocate(101, MemoryZone::GREEN, VGC_State::ACTIVE);

collector.allocate(102, MemoryZone::RED, VGC_State::MARKED);

collector.allocate(103, MemoryZone::BLUE, VGC_State::PERSIST);

collector.allocate(104, MemoryZone::GREEN, VGC_State::IDLE);

collector.allocate(105, MemoryZone::RED, VGC_State::ACTIVE);



collector.display_status();

// Phase 2: Simulating Application Behavior with State Transitions

std::cout << "\\n\\nPhase 2: Simulating Application Runtime Behavior\\n";

collector.transition_state(102, VGC_State::EXPIRED);  // Marked -> Expired

collector.transition_state(104, VGC_State::ACTIVE);   // Idle -> Active

collector.transition_state(105, VGC_State::DEMOTE);   // Active -> Demote candidate



collector.display_status();

// Phase 3: Garbage Collection Sweep

std::cout << "\\n\\nPhase 3: Executing Garbage Collection\\n";



// First sweep with no pending operations

collector.sweep();

collector.display_status();



// Simulate pending operations (e.g., references from recently allocated objects)

std::cout << "\\n\\nPhase 4: Simulating Pending Operations\\n";

collector.allocate(106, MemoryZone::GREEN, VGC_State::ACTIVE);

collector.allocate(107, MemoryZone::RED, VGC_State::ACTIVE);



// Create a pending mask that might affect liveness decisions

uint8_t pending_operations_mask = 0b011;  // Example pending operations



std::cout << "\\nExecuting sweep with pending operations mask: " 

          << static_cast<int>(pending_operations_mask) << "\\n";

collector.sweep(pending_operations_mask);



collector.display_status();



std::cout << "\\n=== Demonstration Complete ===\\n";

std::cout << "Final heap contains " << collector.object_count() 

          << " managed objects.\\n";



return 0;

}